X-Nico

7 unusual facts about Normal distribution


Algorithmic inference

With this law he computes, for instance “the probability that μ (mean of a Gaussian variable – our note) is less than any assigned value, or the probability that it lies between any assigned values, or, in short, its probability distribution, in the light of the sample observed”.

Kees Posthumus

Put differently: the academic requirements adjust themselves to the bell curve.

Kolmogorov–Smirnov test

In the special case of testing for normality of the distribution, samples are standardized and compared with a standard normal distribution.

Log-normal distribution

The distribution is occasionally referred to as the Galton distribution or Galton's distribution, after Francis Galton.

Median absolute deviation

The factor 1.4826\ \approx 1/\left(\Phi^{-1}(3/4)\right) results from the reciprocal of the normal inverse cumulative distribution function, \Phi^{-1}(P), evaluated at probability P=3/4.

Normal law

Normal distribution and the Gaussian law(s) relating to the bell curve

Side lobe

Because an antenna's far field radiation pattern is a Fourier Transform of its aperture distribution, most antennas will generally have sidelobes, unless the aperture distribution is a Gaussian, or if the antenna is so small, as to have no sidelobes in the visible space.


68–95–99.7 rule

In statistics, the 68–95–99.7 rule, also known as the three-sigma rule or empirical rule, states that nearly all values lie within three standard deviations of the mean in a normal distribution.

Andrzej Kajetan Wróblewski

He specializes in elementary particle physics (high energy physics) i.e. Soft Hadron Physics (1990), New AMY and DELPHI multiplicity data and the log-normal distribution (with co-authors; 1990), Genesis of the lognormal multiplicity distribution in the e² e²- collisions and other stochastic processes (with co-authors; 1990), Mystery of the negative binomial distribution (with co-authors; 1987), Constraints on multiplicity distribution of quark pairs (1985).

Gauss–Markov

The Gauss–Markov theorem in mathematical statistics (In this theorem, one does not assume the probability distributions are Gaussian.)

Verification and Validation of Computer Simulation Models

A requirement is that both the system data and model data be approximately Normally Independent and Identically Distributed (NIID).

Wilhelm Johannsen

His findings led him to oppose contemporary Darwinists, most notably Francis Galton and Karl Pearson, who held the occurrence of normal distributed trait variation in populations as proof of gradual genetic variation on which selection could act.


see also

Linear discriminant analysis

Despite limitations including known nonconformance of accounting ratios to the normal distribution assumptions of LDA, Edward Altman's 1968 model is still a leading model in practical applications.

Logistic distribution

Both the United States Chess Federation and FIDE have switched their formulas for calculating chess ratings from the normal distribution to the logistic distribution; see Elo rating system.

Skewness risk

He feels that the extensive reliance on the normal distribution for much of the body of modern finance and investment theory is a serious flaw of any related models (including the Black–Scholes model and CAPM).